README.md

---
title: Twin Track
emoji: 🚀
colorFrom: red
colorTo: red
sdk: docker
app_port: 8501
tags:
- streamlit
pinned: false
short_description: 'Visualization of human vs simulated interaction dynamics '
license: mit
---

# TwinTrack

**Observed vs Simulated Interation Dynamics**

TwinTrack is a lightweight visualization tool for comparing long-form human-LLM interactions against synthetic persona simulations, stripped of semantic content and analyzed purely by temporal shape.

This is not about *what* is said. It is about how interation unfolds over time.

# What TwinTrack Shows

**Top:** A human long-form interaction (Big Flame)
**Bottom:** A selected synthetic persona (Minimalist, Cheerleader, Poet)

Each band visualizes rolling response variance across normalized interaction time.
Same scale. Same normalization. Different dynamics. 

Synthetic personas often look "reasonable" in isolation. When placed next to a human thread, their temporal fingerprints tell a different story. 

# How it Works (High Level)
- Conversation threads are converted to numeric features (length, variance)
- Time is normalized to a 0-1 scale to allow comparison across unequal thread lenghts
- A rolling window computes variance over interaction time
- Tow bands are rendered using a shared color scale for direct visual comparison

No embeddings.
No sentiment labels.
No semantic interpretation.
Just shape. 

# TwinTrack is NOT
- A benchmark
- A performance metric
- A truth or safety score 
- A semantic analyzer

TwinTrack is an instrument - not a verdict

# Status
- v1: Working prototype
- Interaction persona selection
- Normalized temporal alignment
- Shared color scale for interpretability

Future iterations may explore:
- Additional perturbation controls
- Alternative variance measures
- Multi-human baselines

# Related Work
Beyond Content: Temporal Dynamics in Long-Form Human-LLM Interation
DOI: https://doi.org/10.5281/zenodo.18273459